Asymmetric Impact of Matching Technology on Influencer Marketing: Implications for Platform Revenue

Jessie Liu () and Yi Liu ()
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Jessie Liu: Carey Business School, Johns Hopkins University, Baltimore, Maryland 21202
Yi Liu: Wisconsin School of Business, University of Wisconsin–Madison, Madison, Wisconsin 53715

Marketing Science, 2025, vol. 44, issue 1, 65-83

Abstract: This paper explores the impact of using advanced technology such as artificial intelligence (AI) to match marketers with social media influencers. We develop a theoretical model to examine how matching accuracy affects the competition between influencers and the profitability of a social media platform. Our findings show that improving matching accuracy may not always benefit the platform, especially for platforms with intermediate follower density. Two opposing effects of technology improvement affect the prices of influencer marketing campaigns: advanced technology, such as AI, enhances the matching between influencers and marketers and also intensifies competition between different types of influencers. The overall effect on prices can be negative for some influencers because of the asymmetric nature of such matching technology: the matching outcome for influencers with a narrower audience (niche influencers) is more sensitive to matching accuracy than that for those with a broader audience (general influencers). As a result, more niche influencers begin to participate in marketing campaigns when matching accuracy improves, which reduces the prices offered by sufficiently general influencers and may lead to a decline in platform revenue. Additionally, we find that adjusting commission rates in response to technology improvements could help mitigate the negative impact although it may not eliminate it entirely. Our findings offer valuable insights for social media platforms seeking to remain competitive in the influencer marketing landscape.

Keywords: matching; influencer marketing; competition; technology strategy (search for similar items in EconPapers)
Date: 2025
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http://dx.doi.org/10.1287/mksc.2023.0211 (application/pdf)

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Persistent link: https://EconPapers.repec.org/RePEc:inm:ormksc:v:44:y:2025:i:1:p:65-83

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